Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Geophysical Sensing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

Satellite geological and geophysical remote sensing of Iceland

The author has identified the following significant results. Most of the research emphasis was directed at the analysis of Icelandic icecaps on ERTS imagery. A number of new findings were made, including: (1) on low sun angle imagery of Hofsjokull, the outline of a probable central volcano can be seen delineated on the northwest part of the icecap; (2) on low sun angle imagery of Langjokull, two parallel hyaloclastite ridges can be seen to continue for more than 10 km in from the margin of the icecap; (3) measurements of contorted medial moraines on images of Skeioararjokull, acquired about 11 months apart show an approximate 600 m of annual glacier movement; (4) measurements on images of the surging glacier, Eyjabakkajokull, taken about 11 months apart show an approximate 1.8 km of movement during that time; and (5) successive ERTS images of the glacier-dammed lake, Graenalon, show an increase in area of the lake until the ice dam was partially breached, causing a jokulhlaup across the Skeioararsandur. Because of the shape of the lake basin the elevation of the post-jokulhlaup lake can be determined from ERTS imagery to + or - 2 m.

Williams, R. S., Jr.↗

Satellite geological and geophysical remote sensing of Iceland

The author has identified the following significant results. The ERTS imagery has sufficient resolution to map, from MSS color composites, areas of altered ground caused by high temperature geothermal activity at the Namafjall, Torfajokull, and Reykjanes geothermal areas. The major axes of the fallout pattern of tephra from the May - July 1970 volcanic eruption from Hekla Volcano can be mapped where sufficient depth of deposition was present to seriously affect the normal vegetation. Lava flows from the 1961 volcanic eruption at Askja; some of the lava flows from the 1947-48 eruption, and and all of the lava flows from the 1970 eruption at Hekla; and the areas covered by tephra and lava from the 1973 eruption on Heimaey could be delineated. Low sun angle imagery of less than 10 deg of snow covered terrain was particularly valuable in mapping structural and volcanic features concealed beneath glacial ice in the active volcanic zones of Iceland.

Williams, R. S., Jr.↗

Synergistic relationships among remote-sensing and geophysical media: Geological and hydrological applications

Skylab photographs, side-looking radar imagery, published soil maps, topographic maps, conventional aerial photography as well as LANDSAT imagery under wet and dry changes for several years were analyzed over selected areas in Minnesota to test their usefulness in detecting near-surface ground water. Results show that optical density read from LANDSAT data is not a reliable discriminator of depth to shallow ground water when one band of one scene is used alone, and is little improved when several bands of several scenes are used synergistically. The method is enhanced if information from soil maps is included in the analysis, especially for discriminating boggy ground from better drained areas. It appears, however, that in areas where soil maps and good topographic maps already exist, the depth to ground water can be predicted from those media as well as (if not better than) it can be predicted from remote imagery. The LANDSAT method used demonstrated no capability for recognizing deeper categories of ground water.

Southwick, D. L.↗

Optically thin cirrus clouds - Remote sensing, and geophysical significance

The region of the IR spectrum that is ideally suited for detecting optically thin cirrus clouds is in the window between 10 and 13 microns. Here relatively weak absorption due to the water vapor lines and continuum is present and hence the extinction characteristic of the cloud particles is readily discernible. In order to demonstrate these properties, two IR spectra are presented, one with clear skies and one with an optically thin cirrus. As a result of the cloud particle extinction, an appreciable increase in the brightness temperature from 10 to 13 microns is observed. This decrease is found to be nearly linear in the case of the tropical thin cirrus, which is also geometrically thin. On the basis of radiative transfer simulations, it is inferred that the cloud particle size that can produce this spectral character has an effective diameter of about 12 microns, which is comparable to the wavelength of the radiation.

Prabhakara, C.↗

Integration of remote sensing and surface geophysics in the detection of faults

Remote sensing was included in a comprehensive investigation of the use of geophysical techniques to aid in underground mine placement. The primary objective was to detect faults and slumping, features which, due to structural weakness and excess water, cause construction difficulties and safety hazards in mine construction. Preliminary geologic reconnaissance was performed on a potential site for an underground oil shale mine in the Piceance Creek Basin of Colorado. LANDSAT data, black and white aerial photography and 3 cm radar imagery were obtained. LANDSAT data were primarily used in optical imagery and digital tape forms, both of which were analyzed and enhanced by computer techniques. The aerial photography and radar data offered supplemental information. Surface linears in the test area were located and mapped principally from LANDSAT data. A specific, relatively wide, linear pointed directly toward the test site, but did not extend into it. Density slicing, ratioing, and edge enhancement of the LANDSAT data all indicated the existence of this linear. Radar imagery marginally confirmed the linear, while aerial photography did not confirm it.

Jackson, P. L.↗

Airborne Geophysics and Remote Sensing Applied to Study Greenland Ice Dynamics

Overview of project: we combined and jointly analysed geophysical, remote sensing and glaciological data for investigating the temporal changes in ice flow and the role of geologic control on glacial drainage. The project included two different studies, the investigation of recent changes of the Kangerlussuaq glacier and the study of geologic control of ice flow in NW Greenland, around the Humboldt, Petermann and Ryder glaciers.

Csatho, Beata M.↗

Variability of geophysical parameters from aircraft radiance measurements for FIFE

Airborne multispectral images were gathered on two days during the First ISLCP Field Experiment (FIFE) to study the time and space variability of remotely sensed geophysical parameters over the study region. The data sets comprised multiple overflights covering approximately a 60-min period during late morning on 04 June 1987 and shortly after dark on the subsequent day. Image data from each overpass were calibrated and earth-located, with regard to each other, utilizing aircraft INS parameters and ground control points.

Jedlovec, Gary J.↗

The Importance of Accounting for Landscape Position When Investigating Grasslands: A Multidisciplinary Characterisation of a California Coastal Grassland

Abstract Grasslands are one of the most common land‐cover types, providing important ecosystem services globally, yet few studies have examined grassland critical‐zone functioning throughout hillslopes. This study characterised a coastal grassland over a small hillslope at Point Reyes National Seashore, California, using multidisciplinary techniques, combining remotely‐sensed, geophysical, plant, and soil measurements. Clustering techniques delineated the study area into four landscape zones, up‐, mid‐, and down‐slope, and a bordering riparian ecotone, which had distinct environmental properties that varied spatially across the site, with depth, and time. Soil moisture increased with depth and down slope towards a bordering riparian zone, and co‐varied with soil CO 2 flux rates both spatially and temporally. This highlighted three distinct controls of soil moisture on soil respiration: CO 2 fluxes were inhibited by high moisture content in the down‐slope during the wet winter months, and converged across landscape positions in the dry summer months, while also displaying post‐rain pulses. The normalised difference vegetation index (NDVI) ranged from 0.32 (September)–0.80 (April) and correlated positively with soil moisture and aboveground biomass, moving down slope. Yet, NDVI, aboveground biomass, and soil moisture were not correlated to soil organic carbon (SOC) content (0.4%–4.5%), which was highest in the mid‐slope. The SOC content may instead be linked to shifts in dominant grassland species and their rhizosphere properties with landscape position. This multidisciplinary characterisation highlighted significant heterogeneity in grassland properties with landscape position, and demonstrated an approach that could be used to characterise other critical‐zone environments on hillslopes.

54 ENVIRONMENTAL SCIENCES↗

The SMART Cables Initiative for Ocean and Geophysical Observing [Slides]

SMART Cables are becoming a reality, and have the potential to revolutionize submarine oceanographic and geophysical sensing. Pilot / demonstration projects are underway to test the technology and explore the feasibility of incorporating both in-repeater standardized sensor packets but also ancillary sensor types on external, branching nodes. The projects currently in planning will set the standard and influence the norms for the future of SMART systems. The interest of all potential stakeholders and users, and input as to needs and concerns, is welcomed as testing proceeds.

54 ENVIRONMENTAL SCIENCES↗

Calibration, navigation, and registration of MAMS data for FIFE

The International Satellite Land Surface Climatology Project (ISLSCP) was conducted to study the interaction of the atmosphere with the land surface and the research problems associated with the interpretation of satellite data over the Earth's land surface. The experimental objectives of the First ISLSCP Field Experiment (FIFE) were the simultaneous acquisition of satellite, atmospheric, and surface data and to use these data to understand the processes controlling energy/mass exchange at the surface. The experiment site is a 15 x 15 km area southeast of Manhattan, Kansas, intersected by Interstate 70 and Kansas highway 177. The Konza Prairie portion is 5 x 5 km and is a controlled experiment site consisting primarily of native tall grass prairie vegetation. The remainder of the site is grazing and farm land with trees along creek beds that are scattered over the area. Airborne multispectral imagery from the Multispectral Atmospheric Mapping Sensor (MAMS) was collected over this region on two days during Intensive Field Campaign-1 (1FC-1) to study the time and space variability of remotely-sensed geophysical parameters. These datasets consist of multiple overflights covering about a 60-min period during late morning on June 4, 1987 and shortly after dark on the following day. Image data from each overpass were calibrated and Earth located with respect to each other using aircraft inertial navigation system parameters and ground control points. These were the first MAMS flights made with 10-bit thermal data.

Jedlovec, G. J.↗

PAIRS, The GIS-Based Incident Response System for Pennsylvania, and NASA

Over the past several years the Pennsylvania Departments of Environmental Protection (DEP), Health (DOH), and Agriculture (PDA) built the GIs-based Pennsylvania West Nile Surveillance System. That system has become a model for collecting data that has a field component, laboratory component, reporting and mapping component, and a public information component. Given the success of the West Nile Virus System and the events of September 11, 2001, DEP then embarked on the development of the Pennsylvania Incident Response System, or PAIRS. PAIRS is an effective GIs-based approach to providing a system for response to incidents of any kind, including terrorism because it is building upon the existing experience, infrastructure and databases that were successfully developed to respond to the West Nile Virus by DEP, DOH, and PDA. The proposed system can be described as one that supports data acquisition, laboratory forensics, decision making/response, and communications. Decision makers will have tools to view and analyze data from various sources and, at the same time, to communicate with the large numbers of people responding to the same incident. Recent collaborations with NASA partners are creating mechanisms for the PAIRS system to incorporate space-based and other remote sensing geophysical parameters relevant to public health assessment and management, such as surface temperatures, precipitation, land cover/land use change, and humidity. This presentation will describe the PAIRS system and outline the Pennsylvania-NASA collaboration for integration of space-based data into the PAIRS system.

Conrad, Eric↗

Toward Malaria Risk Prediction in Afghanistan Using Remote Sensing

Malaria causes more than one million deaths every year worldwide, with most of the mortality in Sub-Saharan Africa. It is also a significant public health concern in Afghanistan, with approximately 60% of the population, or nearly 14 million people, living in a malaria-endemic area. Malaria transmission has been shown to be dependent on a number of environmental and meteorological variables. For countries in the tropics and the subtropics, rainfall is normally the most important variable, except for regions with high altitude where temperature may also be important. Afghanistan s diverse landscape contributes to the heterogeneous malaria distribution. Understanding the environmental effects on malaria transmission is essential to the effective control of malaria in Afghanistan. Provincial malaria data gathered by Health Posts in 23 provinces during 2004-2007 are used in this study. Remotely sensed geophysical parameters, including precipitation from TRMM, and surface temperature and vegetation index from MODIS are used to derive the empirical relationship between malaria cases and these geophysical parameters. Both neural network methods and regression analyses are used to examine the environmental dependency of malaria transmission. And the trained models are used for predicting future transmission. While neural network methods are intrinsically more adaptive for nonlinear relationship, the regression approach lends itself in providing statistical significance measures. Our results indicate that NDVI is the strongest predictor. This reflects the role of irrigation, instead of precipitation, in Afghanistan for agricultural production. The second strongest prediction is surface temperature. Precipitation is not shown as a significant predictor, contrary to other malarious countries in the tropics or subtropics. With the regression approach, the malaria time series are modelled well, with average R2 of 0.845. For cumulative 6-month prediction of malaria cases, the average provincial accuracy reaches 91%. The developed predictive and early warning capabilities support the Third Strategic Approach of the WHO EMRO Malaria Control and Elimination Plan.

Safi, N.↗

Investigating Microtopographic and Soil Controls on a Mountainous Meadow Plant Community Using High-Resolution Remote Sensing and Surface Geophysical Data

Our study aims to explore the microtopographic controls that dictate the heterogeneity of plant communities in a mountainous floodplain-hillslope system, using remote sensing and surface geophysical techniques. Working within a lower montane floodplain-hillslope study site (750 m × 750 m) in the Upper Colorado River Basin, we developed a new data fusion framework, based on machine learning and feature engineering, that exploits remote sensing optical and light detection and ranging (LiDAR) data to estimate the distribution of key plant meadow communities at submeter resolution. We collected surface electrical resistivity tomography data to explore the variability in soil properties along a floodplain-hillslope transect at 0.50-m resolution and extracted LiDAR-derived metrics to model the rapid change in microtopography. Furthermore, we investigated the covariability among the estimated plant community distributions, soil information, and topographic metrics. Results show that our framework estimated the distribution of nine plant communities with higher accuracy (87% versus 80% overall; 85% versus 60% for shrubs) compared to conventional classification approaches. Analysis of the covariabilities reveals a strong correlation between plant community distribution, soil electric conductivity, and slope, indicating that soil moisture is a primary control on heterogeneous spatial distribution. At the same time, microtopography plays an important role in creating particular ecosystem niches for some of the communities. Such relationships could be exploited to provide information about the spatial variability of soil properties. This highly transferable framework can be employed within long-term monitoring to capture community-specific physiological responses to perturbations, offering the possibility of bridging local plot-scale observations with large landscape monitoring.

54 ENVIRONMENTAL SCIENCES↗

From Grain to Floodplain: Evaluating heterogeneity of floodplain hydrostatigraphy using sedimentology, geophysics, and remote sensing

Stratigraphy is a fundamental component of floodplain heterogeneity and hydraulic conductivity and connectivity of alluvial aquifers, which affect hydrologic processes such as groundwater flow and hyporheic exchange. Watershed–scale hydrological models commonly simplify the sedimentology and stratigraphy of floodplains, neglecting natural floodplain heterogeneity and anisotropy. This study, conducted in the upper reach of the East River in the East River Basin, Colorado, USA, combines point–, meander–, and floodplain–scale data to determine key features of alluvial aquifers important for estimating hydrologic processes. We compare stratigraphy of two meanders with disparate geometries to explore floodplain heterogeneity and connectivity controls on flow and transport. Meander shape, orientation, and internal stratigraphy affected residence time estimates of laterally exchanged hyporheic water. Although the two meanders share a sediment source, vegetation, and climate, their divergent river migration histories resulted in contrasting meander hydrofacies. In turn, the extent and orientation of these elements controlled the effective hydraulic conductivity and, ultimately, estimates of groundwater transport and hyporheic residence times. Additionally, the meanders’ orientation relative to the valley gradient impacted the hydraulic gradient across the meanders—a key control of groundwater velocity. In conclusion, we combine our field data with remotely sensed data and introduce a potential approach to estimate key hydrostratigraphic packages across floodplains. Prospective applications include contaminant transport studies, hyporheic models, and watershed models.

58 GEOSCIENCES↗

International Geoscience and Remote Sensing Symposium, Washington, DC, June 8-10, 1981, Digest. Volumes 1 & 2

Sensors used for the geophysical and remote sensing studies are reviewed; in particular, NIMBUS-7 Scanning Multichannel Microwave Radiometer results are given. Remote sensing analyses consider such areas as hydrology, soil moisture, and planetary surfaces. In addition, Shuttle remote sensing experiments and SAR systems, remote sensing in the thermal infrared, and microwave remote sensing of the earth are considered. Finally, attention is given to lithologic and geobotanical studies, and geophysical sensing techniques and inversion theory.

Source record↗

Introduction to this special section: Geophysical applications of fiber-optic distributed sensing

Here, this special section is dedicated to geophysical distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) applications. Since the introduction of commercial DTS units in the 1980s and more recent deployment of DAS in this decade, distributed sensing is quietly revolutionizing sectors of geophysics, particularly those requiring permanent downhole measurements. The common component of distributed sensing technologies is the use of laser scattering measurements on fiber-optic cables (tens of kilometers long) to estimate the physical state of each fiber segment with measurands including temperature (DTS), static strain (DSS), and, most recently, dynamic strain and seismic waves (DAS) recorded either continuously or on an as-needed basis. The high spatial coverage, accuracy, and resolution of this technology make it a truly groundbreaking addition to our subsurface sensing toolbox.

47 OTHER INSTRUMENTATION↗

Quantifying and relating land-surface and subsurface variability in permafrost environments using lidar and surface geophsical datasets

The complexity of permafrost dynamics and its critical impact on climate feedbacks warrant continued development of advanced high-latitude terrestrial ecosystem characterization and monitoring approaches. In this study, we explore the value of remote sensing and surface geophysical data for characterizing land surface and subsurface properties and their linkages in an Alaskan Coastal Plain ecosystem. We base our study on data collected at the end of the 2011 growing season in the Barrow Environmental Observatory, where a nested suite of measurements were collected within a polygon-dominated region including: surface ground penetrating radar, electromagnetic, and electrical resistance tomography data; thaw depth, soil temperature and moisture content, soil texture, soil carbon and nitrogen content, and major and trace cations. Previously-collected lidar data were also available for the study. Analysis of the datasets, individually and in combination, revealed the utility of the methods for characterizing critical land-surface and subsurface properties and associated spatial zonation. Lidar analysis was performed to extract geomorphic metrics (such as slope, curvature, and directed distance of polygons), which potentially indicate drainage potential and permafrost deformation state. Cluster analysis of these lidar-obtained attributes suggested that the land surface can be grouped into three spatially coherent zones, each having a dominant geomorphic expression including: a high centered polygon zone, a low centered polygon zone and a transitional zone. Comparison of the geophysical attributes from radar, electrical resistance tomography, and electromagnetic data with point measurements suggests that the surface geophysical data can provide very high-resolution information about subsurface properties that affect ecosystem feedbacks to climate, such as thaw depth and moisture content. Cluster analysis suggested that the geophysical attributes also varied spatially in a systematic way, suggesting the presence of three laterally distinct subsurface zones. Analysis of zone-based subsurface point measurements suggests that the geophysically-defined zones have unique distributions of hydrological, thermal, and geochemical properties and that the subsurface (geophysically-based) and land-surface (lidar-based) zonation is consistent. Although the close linkage between land surface (polygonal geomorphology) and subsurface (active layer) variability revealed through our study is not surprising, to our knowledge this is the first study to document such relationships using high resolution and non-invasive approaches. This study suggests the potential of using coincident lidar and surface geophysical measurements to quantify land surface and subsurface properties (respectively) and their linkages, which are likely to play a role in terrestrial ecosystem evolution and feedbacks to climate. These findings open the way for future research focused on using combined geophysical and remote sensing datasets to estimate subsurface and land-surface properties in high resolution and over large regions as is needed for process understanding and numerical model initialization in high latitude terrestrial ecosystems.

Climate↗